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Koji Yokote

dblp:163/3077 · DBLP profile ↗
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4ranked-venue papers
2as first author
3since 2021 · last 2025
0000-0002-9539-748XORCID · corroborated

Domains — the database's venue-derived domains; a paper can count in several

Theory of computation · 4 · 2 first-author · 3 since 2021Artificial intelligence and machine learning · 2 · 1 first-author · 2 since 2021

Expertise — from the expertise taxonomy: the topics of the expert's papers under the CCF categories. A weight counts papers with recency: 1 for a paper about the topic, 0.3 when the topic is its context, halved every five years.

Theoretical computer science
2 papers
Algorithmic game theory and mechanism design · 76% Combinatorics and discrete mathematics · 19% Mathematical optimization · 6%

Topics — the 5 heaviest of 6, each with the papers that count most for it

TopicWeightPapersLastEvidence papers
Algorithmic game theory and mechanism design
distributional objectives
0.912025
Market Design with Distributional Objectives · EC 2025
Algorithmic game theory and mechanism design
market design
0.912025
Market Design with Distributional Objectives · EC 2025
Combinatorics and discrete mathematics
matroid
0.912025
Market Design with Distributional Objectives · EC 2025
Algorithmic game theory and mechanism design › social choice › social choice function
path independence
0.912025
Rationalizing Path-Independent Choice Rules · EC 2025
Algorithmic game theory and mechanism design › non-cooperative game › strategic game
rationalizability
0.912025
Rationalizing Path-Independent Choice Rules · EC 2025

Methods — techniques the papers use, named apart from their topics

utility theory · 0.9mechanism design · 0.9discrete convex analysis · 0.9
YearPublicationVenuePosition
2025 Market Design with Distributional Objectives
abstract
We provide optimal solutions to an institution that has distributional objectives when choosing from a set of applications based on merit (or priority). For example, in college admissions, administrators may want to admit a diverse class in addition to choosing students with the highest qualifications. We provide a family of choice rules that maximize merit subject to attaining a level of the distributional objective. We study the desirable properties of choice rules in this family and use them to find all subsets of applications on the Pareto frontier of the distributional objective and merit. In addition, we provide two novel characterizations of matroids. A full version is available at https://arxiv.org/abs/2301.00237.
Isa Emin Hafalir, Fuhito Kojima, M. Bumin Yenmez, Koji Yokote
EC4
2025 Rationalizing Path-Independent Choice Rules
abstract
Path independence is arguably one of the most important choice rule properties in economic theory. We show that a choice rule is path independent if and only if it is rationalizable by a utility function satisfying ordinal concavity, a concept closely related to concavity notions in discrete mathematics. We also provide a rationalization result for choice rules that satisfy path independence and the law of aggregate demand. A full version is available at https://arxiv.org/abs/2303.00892.
Koji Yokote, Isa Emin Hafalir, Fuhito Kojima, M. Bumin Yenmez
EC1
2025 A note on ordinally concave functions
Satoru Fujishige, Fuhito Kojima, Koji Yokote
Discret. Appl. Math.3
2020 The discrete separation theorem and price adjustment directions in markets with heterogeneous commodities
Koji Yokote
Discret. Appl. Math.1